Responses of Microbial Community to Heterogeneous Dissolved Organic Nitrogen Constituents in the Hyporheic Zones of Treated Sewage-Dominated Rivers.

Journal: Microbial ecology
Published Date:

Abstract

The hyporheic zone (HZ) of treated sewage-dominated rivers serves as a critical biogeochemical hotspot for dissolved organic nitrogen (DON) transformation, yet the mechanisms linking DON chemodiversity to microbial community dynamics remain poorly resolved. This study integrated spectroscopic fingerprinting, machine learning, and partial least squares path modeling (PLS-PM) to unravel the interactions between redox-stratified DON fractions and microbial consortia in two effluent-impacted rivers (Xi'an, China). The results revealed that DOM spectral parameters associated with distinct DON characteristics posed distinct effects on microbial communities, with the communities in oxic zones largely impacted by autobiogenic, aromatic, and protein-like DON, while the communities in suboxic zones were more intensely impacted by the humification degree of DON. Microbial communities exhibited redox-dependent niche differentiation; i.e., keystone taxa in oxic zones (e.g., Gamma-Proteobacteria) drove nitrogen assimilation, while suboxic taxa (e.g., Verrucomicrobia) prioritized stress-resistant D-amino acid metabolism. PLS-PM demonstrated that biomarkers exerted stronger control on nitrogen cycling (|path coefficients|> 0.6, P < 0.05) than keystone taxa, with summer communities showing higher model fit. Treated sewage-derived DON fostered specialized consortia through biochemical trade-offs, i.e., methionine recycling in oxic zones versus peptidoglycan modification in suboxic zones, thus highlighting the critical role of HZ in mitigating nitrogen pollution. These findings advance predictive modeling of DON-microbe interactions in anthropogenically perturbed aquatic ecosystems.

Authors

  • Tao He
  • Yudong Chen
    College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China; The National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen 518060, China.
  • Yutao Wang
    Affiliated Hospital of Medical School, Ningbo University, Ningbo 315020, China.
  • Zongyi Peng
    China Yangtze Power Co, Ltd. (CYPC), Wuhan, 430000, China.
  • You Mou
    China Yangtze Power Co, Ltd. (CYPC), Wuhan, 430000, China.
  • Longfei Wang
    The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.